| Towards fully autonomous driving: Systems and algorithms J Levinson, J Askeland, J Becker, J Dolson, D Held, S Kammel, JZ Kolter, ... 2011 IEEE intelligent vehicles symposium (IV), 163-168, 2011 | 1855 | 2011 |
| Constrained policy optimization J Achiam, D Held, A Tamar, P Abbeel International conference on machine learning, 22-31, 2017 | 1670 | 2017 |
| Learning to track at 100 fps with deep regression networks D Held, S Thrun, S Savarese Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 1565 | 2016 |
| Pcn: Point completion network W Yuan, T Khot, D Held, C Mertz, M Hebert 2018 international conference on 3D vision (3DV), 728-737, 2018 | 1060 | 2018 |
| Automatic goal generation for reinforcement learning agents C Florensa, D Held, X Geng, P Abbeel International conference on machine learning, 1515-1528, 2018 | 592* | 2018 |
| Reverse curriculum generation for reinforcement learning C Florensa, D Held, M Wulfmeier, M Zhang, P Abbeel Conference on robot learning, 482-495, 2017 | 534 | 2017 |
| 3d multi-object tracking: A baseline and new evaluation metrics X Weng, J Wang, D Held, K Kitani 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 461 | 2020 |
| Softgym: Benchmarking deep reinforcement learning for deformable object manipulation X Lin, Y Wang, J Olkin, D Held Conference on Robot Learning, 432-448, 2021 | 234 | 2021 |
| Enabling robots to communicate their objectives SH Huang, D Held, P Abbeel, AD Dragan Autonomous Robots 43, 309-326, 2019 | 186 | 2019 |
| Plas: Latent action space for offline reinforcement learning W Zhou, S Bajracharya, D Held Conference on Robot Learning, 1719-1735, 2021 | 185 | 2021 |
| Just go with the flow: Self-supervised scene flow estimation H Mittal, B Okorn, D Held Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 172 | 2020 |
| What you see is what you get: Exploiting visibility for 3d object detection P Hu, J Ziglar, D Held, D Ramanan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 148 | 2020 |
| Adaptive auxiliary task weighting for reinforcement learning X Lin, H Baweja, G Kantor, D Held Advances in neural information processing systems 32, 2019 | 132 | 2019 |
| Ab3dmot: A baseline for 3d multi-object tracking and new evaluation metrics X Weng, J Wang, D Held, K Kitani arXiv preprint arXiv:2008.08063, 2020 | 121 | 2020 |
| Combining 3D Shape, Color, and Motion for Robust Anytime Tracking D Held, J Levinson, S Thrun, S Savarese Robotics: Science and Systems, 2014 | 120* | 2014 |
| Learning visible connectivity dynamics for cloth smoothing X Lin, Y Wang, Z Huang, D Held Conference on Robot Learning, 256-266, 2022 | 119 | 2022 |
| Fabricflownet: Bimanual cloth manipulation with a flow-based policy T Weng, SM Bajracharya, Y Wang, K Agrawal, D Held Conference on Robot Learning, 192-202, 2022 | 90 | 2022 |
| Flowbot3d: Learning 3d articulation flow to manipulate articulated objects B Eisner, H Zhang, D Held arXiv preprint arXiv:2205.04382, 2022 | 88 | 2022 |
| Precision Tracking with Sparse 3D and Dense Color 2D Data D Held, J Levinson, S Thrun | 84 | 2013 |
| Safe local motion planning with self-supervised freespace forecasting P Hu, A Huang, J Dolan, D Held, D Ramanan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 80 | 2021 |
Pieter AbbeelUC Berkeley | CovariantDirección de correo verificada de cs.berkeley.edu
